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Topological Data Analysis Jobs in California (NOW HIRING)

Develop and maintain CAD modeling algorithms (editing brep data structures, developing topological ... Analyze code for performance and optimization opportunities as it relates to load times, memory ...

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Topological Data Analysis information

What is a topological data analysis?

A Topological Data Analysis (TDA) job involves applying concepts from topology, a branch of mathematics, to analyze and extract insights from complex data. Professionals in this field use techniques like persistent homology and mapper algorithms to uncover hidden structures in high-dimensional datasets. They often work in industries such as bioinformatics, finance, and machine learning, helping to interpret data patterns that traditional methods might miss. TDA specialists typically have expertise in mathematics, data science, and programming, using tools like Python, R, and specialized libraries such as Gudhi or Ripser.

What are the key skills and qualifications needed to thrive in topological data analysis, and why are they important?

To thrive in Topological Data Analysis, you need a strong background in mathematics (especially algebraic topology), statistical analysis, and data science, often supported by an advanced degree in math, computer science, or a related field. Proficiency with programming languages like Python or R, and familiarity with topological data analysis (TDA) tools such as GUDHI or Ripser, are highly valuable. Critical thinking, curiosity, and effective communication help you translate complex topological findings into actionable insights for interdisciplinary teams. These skills ensure accurate interpretation of complex data shapes and facilitate meaningful contributions to projects in fields like bioinformatics, finance, or machine learning.

How does topological data analysis typically collaborate with other departments or teams within an organization?

Professionals working in Topological Data Analysis often collaborate closely with data scientists, domain experts, and software engineers to translate abstract topological results into practical solutions. You may contribute to interdisciplinary research, provide insights during project planning meetings, and help interpret complex data structures uncovered through TDA methods. Regular communication and collaborative problem-solving are essential, as you’ll frequently explain technical concepts to non-specialists and incorporate their feedback into analysis workflows. This collaborative environment fosters innovation and ensures that TDA findings are effectively integrated into broader analytical and business strategies.

What are the most commonly searched types of Topological Data Analysis jobs in California?

The most popular types of Topological Data Analysis jobs in California are:

What job categories do people searching Topological Data Analysis jobs in California look for?

The top searched job categories for Topological Data Analysis jobs in California are:

Infographic showing various Topological Data Analysis job openings in California as of August 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 90% In-person, and 10% Remote job distribution.

Senior Principal, Design Engineering

Celestica Inc.

San Jose, CA • On-site

$210 - $320/hr

Other

Re-posted yesterday


Celestica rating

8.8

Company rating: 8.8 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

14th of 159 rated electronics manufacturers


Job description

Senior Principal, Design Engineering

Date: Jul 17, 2026

Location: San Jose, CA, US

Summary

We are seeking a high-impact, visionary Senior Principal AI Engineer to architect, design, and oversee the next generation of our enterprise hardware intelligence platform. In this role, you will be the change agent across our global R&D organization, bridging the gap between advanced Generative AI and complex hardware engineering. Reporting into the Office of the VP of Engineering, you will spearhead the technical development of our Celestica-Tuned Enterprise LLM, transforming massive, highly complex repositories of global engineering data into active, predictive, and autonomous design intelligence.

This is a high impact, high visibility technology role. You will serve as the lead and technical authority responsible for building the domain-specific data pipelines and architecting the cutting-edge Topological and Spatial Retrieval-Augmented Generation (RAG) frameworks. Your mission is to develop a secure, multi-agent AI system and build a digital twin of the hardware design process, enabling real-time simulation and predictive analysis of board performance. This system enables engineering teams to interact natively with design tools and legacy knowledge. Working closely with hardware Subject Matter Experts (SMEs), you will translate schematics, layouts, board logs, and multi-tool diagrams into an intelligent platform that our designers use daily to eliminate board spins, automate compliance, and drastically accelerate time-to-market.

Responsibilities
  • Drive Strategic AI Implementation: Set the technical standard for secure LLM applications within Celestica, utilizing advanced proprietary data and secure infrastructure to build a highly reliable, zero-hallucination platform for high-stakes engineering.
  • Develop Digital Twin Capabilities: Architect and integrate digital twin models to simulate and validate physical hardware performance, enabling virtual prototyping and early design cycle optimization.
  • Architect & Code the Platform: Act as the primary hands‑on developer to design, build, and deploy a multi‑database, topology‑aware RAG system capable of accurately vectorizing complex hardware design data.
  • Build End‑to‑End AI Pipelines: Create specialized parsers and ingestion pipelines that translate dense binary files, netlists, and graphical schematics into high‑dimensional graph‑based semantic embeddings.
  • Develop Multi‑Agent Orchestrations: Leverage advanced orchestration frameworks and the Model Context Protocol (MCP) to develop autonomous AI agents that can manage multi‑tool workflows across synthesis, physical placement, and manufacturing sign‑off.
  • Integrate Cross‑Domain Data: Engineer data lakes that seamlessly correlate unstructured text (supply chain metadata, manufacturing datasheets, standard compliance checks) with physical engineering physics (layout geometries, pin connectivity).
  • Collaborate with Hardware SMEs: Work side‑by‑side with Principal Hardware, SI/PI, and Thermal Engineers to encode deep domain expertise, design rules, and hardware guardrails directly into the AI system’s "Agent Skills."
Compensation

The stated range includes Base Salary and target Short‑Term Incentive (STI) compensation only. A comprehensive benefits package is offered in addition to this range.

The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.

Education

Required Education

Master’s degree (M.S.) in Computer Science, Data Science, Electrical Engineering, or a closely related technical discipline is required. A Ph.D. specializing in AI/ML/DL, Agentic AI or Data Science is highly preferred.

Preferred Education

  • Advanced AI Expertise: Deep experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs).
Qualifications

Required Experience

  • Industry Experience: 10+ years of rigorous software engineering experience, including a minimum of 5 years of dedicated, hands‑on production coding in Large Language Model (LLM) application development, Natural Language Processing (NLP), or advanced Machine Learning architectures.
  • Hardware Lifecycle Engineering: Proven track record of architecting and deploying AI‑driven tools specifically tailored for the Electronic Design Automation (EDA) and hardware engineering lifecycle. You must understand how to ingest and manipulate complex hardware data (e.g., schematics, PCB layouts, netlists, and BOMs).
  • Advanced Technical Stack: Expert‑level coding proficiency in Python and deep learning frameworks (PyTorch/TensorFlow). Proven ability to design, build, and scale high‑performance vector databases (e.g., ChromaDB, Milvus, Pinecone).
  • AI/LLM Mastery: Mastery of advanced LLM orchestration and agentic frameworks (e.g., LangChain, LlamaIndex). Demonstrated experience building complex, multi‑database Retrieval‑Augmented Generation (RAG) pipelines and autonomous multi‑agent systems.

Preferred Experience

  • Advanced AI Expertise: Deep experience in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs).
  • Modern AI Tools & Agents: Strong familiarity with the latest LLMs and autonomous AI agents (e.g., Glean, Gemini Enterprise, Vertex AI, and Anthropic Claude).
  • Hardware Engineering Lifecycle: Comprehensive understanding of the end‑to‑end hardware engineering process for hyperscalers, including schematics, Signal Integrity (SI), Power Integrity (PI), PCB layout, thermal, and mechanical design.
  • EDA & CAD Software: Familiarity with industry‑leading Electronic Design Automation (EDA) and engineering tools (e.g., Cadence Allegro, Siemens EDA, Cadence Sigrity, Keysight ADS, PTC Creo, and Simcenter Flotherm).
Notes

This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.

Equal Employment Opportunity

Celestica is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws. This policy applies to hiring, promotion, discharge, pay, fringe benefits, job training, classification, referral and other aspects of employment and also states that retaliation against a person who files a charge of discrimination, participates in a discrimination proceeding, or otherwise opposes an unlawful employment practice will not be tolerated. All information will be kept confidential according to EEO guidelines. Celestica is an E‑Verify employer.

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